Toward a Shared Vocabulary: Lessons from Employer Standards

Having a shared vocabulary across the learn-and-work ecosystem is critical, as it ensures a common understanding among all stakeholders that improves clarity and boosts the impact of the terms used.

Why Shared Language in the Ecosystem Matters 

Across the learn-and-work ecosystem, a growing number of stakeholders, from education providers and employers to policymakers and technology platforms, are developing new approaches to prepare people for opportunity. However, even as collaboration expands, our shared language remains underdeveloped and fragmented. Take credentials, for example: Although they may share the same name, they often differ widely in purpose, characteristics and the way learning is assessed. 

At the Learn & Work Ecosystem Library and at Workcred, we face this challenge every day. Glossary terms—used in project descriptions, organizational entries, blog posts and digital tags—shape how we create, discover and understand content. Glossary development is not a peripheral task—it’s core to communication and knowledge infrastructure—and it can ultimately affect workplace performance. 

However, there’s still no standardized glossary for this ecosystem, and it’s unclear whether one is even on the horizon. That’s not necessarily surprising. The learn-and-work ecosystem includes a wide range of fields, each with its own language, priorities and frameworks, but one stakeholder group—employers—has made more progress than most in aligning terminology and work specifications. Its success has been driven by needs for global trade, interoperability and a culture of performance-based standards. 

Could that progress point the way for the rest of the ecosystem? Or is employer use of standard terms so distinct that other sectors like education and policy will continue to operate with their own variations? This blog explores that question. 

What Would Standardization Actually Mean? 

At first glance, standardizing glossary terms might seem like an editorial task, but meaningful standardization would involve much more, such as: 

• Selecting preferred terms for key concepts 

• Identifying and mapping synonyms and variant phrases 

• Offering contextualized definitions based on real-world use  

• Clarifying relationships among terms (e.g., broader vs. narrower) 

• Applying terms consistently in metadata and search functions 

• Making credential characteristics transparent and comparable 

Take the term “certification.” While there are existing national and international standards, such as ISO/IEC 17024 and the NCCA Accreditation Standards, different sectors use the term inconsistently. It might refer to anything from a brief training course plus exam, to a legally defensible process with recertification requirements, a code of conduct and even revocation policies for unethical behavior.  

These distinctions matter. Blurred definitions can confuse learners, employers and policymakers, and they also impede interoperability between systems and limits data comparability.  

What Employers Are Doing Differently 

Employers, especially in globally integrated industries, have long embraced standardization. Organizations like ANSI, along with their global counterparts, facilitate frameworks for standardized terminology and job requirements in fields like engineering, cybersecurity, healthcare and other industry sectors. These standards enable alignment across geographic borders and among vendors, suppliers and regulators. 

Why have employers made more progress? 

• Market incentives: Inconsistent language can undermine quality assurance and increase risk in hiring and operations. 

• Global trade: Many employers operate internationally and require conformity in credentials, roles, processes and products.  

• Standards infrastructure: Employer associations often work with national and international bodies to codify job functions, credentials and training. 

This progress raises the question: Can—or should—other sectors follow a similar path? 

How the Library and Workcred Approach Glossary Development 

At both the Learn & Work Ecosystem Library and Workcred, we aren’t aiming to impose a universal language. Instead, we focus on making the current variations visible, understandable and usable. The library maintains a robust, living glossary, currently with nearly 600 terms. These terms support our content architecture, powering filters, search tools and our AI Library Assistant bot. Terms like “skills-based hiring,” “nondegree credential,” “learning and employment record (LER),” and “intermediary organization” are defined with clarity and context. 

Glossary entries include: 

• A stakeholder-informed definition 

• Examples and usage context 

• Related terms and resources 

• Metadata tagging to aid search, filtering and indexing 

 The library also offers the following three glossary formats: 

1. A–Z Glossary: alphabetical term list
2. Glossary by Category: terms grouped by key components of the ecosystem and subcategories  
3. Glossary of Abbreviations: acronyms and short-form references  

A free glossary widget is also available for organizations to embed on their own sites, and several have already done so. Meanwhile, Workcred’s role as an ANSI affiliate means it is engaged in developing credential-related standards and terminology. Workcred not only analyzes how employers and issuers use credentials but also explores how shared terms can improve quality assurance across systems, transparency and trust. 

This work supports better communication across credentialing systems, including degrees, certifications, certificates, state licensure and corporation-issued credentials. 

Why AI and Human Users Both Benefit 

For the Library’s AI Library Assistant bot to interpret user queries effectively, it must grasp the use of similar terms (synonymy), context and term relationships. A user typing “skills-first hiring” should receive the same results as one using “skills-based hiring,” but this requires a bot that can: 

• Recognize alternate phrases (synonym management) 

• Connect search to real-world usage (contextual relevance) 

• Clarify terms with overlapping meanings, e.g., certificate vs. certification (disambiguation) 

These capabilities don’t just serve the bot; they make the system more useful for all users, improving search accuracy and content discovery. These improvements benefit human users too, making the library easier to navigate and more useful as a knowledge and decision support tool. 

Continuous Updates—and Collective Progress 

Glossary development is not a one-time task. New terms emerge constantly, from policy papers, innovation labs, new programs and practitioners. The prescription for currency is the following:   

• Continuously review and refine entries

• Gather feedback from users and partners

• Monitor shifts in ecosystem terminology

Ultimately, glossary work is about building bridges across communities, not gatekeeping language. 

Toward a Shared Vocabulary—Or at Least a Shared Understanding 

While a single, unified vocabulary across the learn-and-work ecosystem may be out of reach any time soon, we can still improve clarity in our language use and alignment. Glossary tools built with both technical rigor and stakeholder input can enhance navigation, search and collaboration throughout the ecosystem. Employers may point the way for us. Their need for standards has led to real-world progress that others might learn from. 

Whether the ecosystem eventually unifies its language or simply learns to translate across groups better, greater clarity, coordination and impact are within reach.